Summary The main goal of this project is to enhance the understanding of the processes and dynamics linking urban growth to population health in order to identify promising policies and interventions to promote health in cities all over the world. By 2030, around 60% of the world's population is expected to live in urban areas. With the increase in chronic diseases and the re-emergence of infectious diseases in urban cores in the developing world, there is an urgent need to understand the health consequences of this urban growth and how it could be managed to promote population health. Cities are complex systems where the density of social interactions generates emergent phenomena, including the scaling properties of urban features. Previous research in the complex systems literature has shown how social outputs such as wealth, crime and innovation scale super-linearly (grow more than expected with city size), meaning that their per capita rate is larger in larger cities due to increased amount of social contacts because of network effects. On the other hand, physical infrastructure such as the length of the road network or the number of gas stations scale sub-linearly (grow less than expected) due to increased efficiency thanks to economies of scale. This proposal aims to: (1) study the scaling properties of nine health outcomes in a heterogeneous sample of 718 cities in the US and 10 Latin American countries; (2) investigate the underlying correlates of the scaling properties of these health outcomes; and (3) develop a system dynamics model to understand the mechanisms behind the scaling properties of health outcomes, to generate hypotheses for future studies. Data for Latin America in Aims 1 and 2 will be obtained from the SALURBAL study, a collaboration of 15 institutions in 10 Latin American countries (Mexico, Guatemala, El Salvador, Nicaragua, Costa Rica, Colombia, Peru, Chile, Brazil and Argentina), led by Drexel University. US data for Aim 1 will be obtained from the NCHS, while US Aim 2 data will be obtained from the RECVD study (1R01AG049970). Aim 3 will use data and parameters from Aims 1 and 2. Given the rapid rate of urbanization globally, our results will have broad implications for understanding of the drivers of urban health worldwide and for urban policies to promote population health. This study will help the investigator to jumpstart a career in complex systems epidemiology and urban health, leveraging and deepening his training in both fields and allowing the investigator to achieve research independence in one of the most promising interdisciplinary collaborative environments in the field of urban health.